Dataset statistics
| Number of variables | 16 |
|---|---|
| Number of observations | 157 |
| Missing cells | 51 |
| Missing cells (%) | 2.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 19.8 KiB |
| Average record size in memory | 128.8 B |
Variable types
| Categorical | 4 |
|---|---|
| Numeric | 12 |
Model has a high cardinality: 156 distinct values | High cardinality |
Latest_Launch has a high cardinality: 130 distinct values | High cardinality |
four_year_resale_value is highly correlated with Price_in_thousands and 6 other fields | High correlation |
Price_in_thousands is highly correlated with four_year_resale_value and 6 other fields | High correlation |
Engine_size is highly correlated with four_year_resale_value and 9 other fields | High correlation |
Horsepower is highly correlated with four_year_resale_value and 8 other fields | High correlation |
Wheelbase is highly correlated with Engine_size and 5 other fields | High correlation |
Width is highly correlated with Engine_size and 7 other fields | High correlation |
Length is highly correlated with Engine_size and 5 other fields | High correlation |
Curb_weight is highly correlated with four_year_resale_value and 9 other fields | High correlation |
Fuel_capacity is highly correlated with four_year_resale_value and 9 other fields | High correlation |
Fuel_efficiency is highly correlated with four_year_resale_value and 8 other fields | High correlation |
Power_perf_factor is highly correlated with four_year_resale_value and 7 other fields | High correlation |
four_year_resale_value is highly correlated with Price_in_thousands and 3 other fields | High correlation |
Price_in_thousands is highly correlated with four_year_resale_value and 4 other fields | High correlation |
Engine_size is highly correlated with four_year_resale_value and 8 other fields | High correlation |
Horsepower is highly correlated with four_year_resale_value and 6 other fields | High correlation |
Wheelbase is highly correlated with Width and 3 other fields | High correlation |
Width is highly correlated with Engine_size and 7 other fields | High correlation |
Length is highly correlated with Engine_size and 4 other fields | High correlation |
Curb_weight is highly correlated with Price_in_thousands and 8 other fields | High correlation |
Fuel_capacity is highly correlated with Engine_size and 6 other fields | High correlation |
Fuel_efficiency is highly correlated with Engine_size and 5 other fields | High correlation |
Power_perf_factor is highly correlated with four_year_resale_value and 7 other fields | High correlation |
four_year_resale_value is highly correlated with Price_in_thousands and 2 other fields | High correlation |
Price_in_thousands is highly correlated with four_year_resale_value and 3 other fields | High correlation |
Engine_size is highly correlated with Horsepower and 5 other fields | High correlation |
Horsepower is highly correlated with four_year_resale_value and 5 other fields | High correlation |
Wheelbase is highly correlated with Width and 2 other fields | High correlation |
Width is highly correlated with Engine_size and 3 other fields | High correlation |
Length is highly correlated with Wheelbase and 2 other fields | High correlation |
Curb_weight is highly correlated with Price_in_thousands and 8 other fields | High correlation |
Fuel_capacity is highly correlated with Engine_size and 2 other fields | High correlation |
Fuel_efficiency is highly correlated with Engine_size and 4 other fields | High correlation |
Power_perf_factor is highly correlated with four_year_resale_value and 5 other fields | High correlation |
Manufacturer is highly correlated with four_year_resale_value and 7 other fields | High correlation |
Sales_in_thousands is highly correlated with Wheelbase and 1 other fields | High correlation |
four_year_resale_value is highly correlated with Manufacturer and 5 other fields | High correlation |
Vehicle_type is highly correlated with Wheelbase and 4 other fields | High correlation |
Price_in_thousands is highly correlated with Manufacturer and 8 other fields | High correlation |
Engine_size is highly correlated with Manufacturer and 9 other fields | High correlation |
Horsepower is highly correlated with Manufacturer and 9 other fields | High correlation |
Wheelbase is highly correlated with Sales_in_thousands and 8 other fields | High correlation |
Width is highly correlated with Vehicle_type and 8 other fields | High correlation |
Length is highly correlated with Manufacturer and 7 other fields | High correlation |
Curb_weight is highly correlated with four_year_resale_value and 10 other fields | High correlation |
Fuel_capacity is highly correlated with Manufacturer and 11 other fields | High correlation |
Fuel_efficiency is highly correlated with Manufacturer and 9 other fields | High correlation |
Power_perf_factor is highly correlated with Manufacturer and 8 other fields | High correlation |
four_year_resale_value has 36 (22.9%) missing values | Missing |
Price_in_thousands has 2 (1.3%) missing values | Missing |
Curb_weight has 2 (1.3%) missing values | Missing |
Fuel_efficiency has 3 (1.9%) missing values | Missing |
Power_perf_factor has 2 (1.3%) missing values | Missing |
Model is uniformly distributed | Uniform |
Latest_Launch is uniformly distributed | Uniform |
Sales_in_thousands has unique values | Unique |
Reproduction
| Analysis started | 2022-04-21 16:17:50.268776 |
|---|---|
| Analysis finished | 2022-04-21 16:18:37.768508 |
| Duration | 47.5 seconds |
| Software version | pandas-profiling v3.1.0 |
| Download configuration | config.json |
| Distinct | 30 |
|---|---|
| Distinct (%) | 19.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 1.4 KiB |
| Dodge | |
|---|---|
| Ford | |
| Toyota | 9 |
| Chevrolet | 9 |
| Mercedes-B | 9 |
| Other values (25) |
Length
| Max length | 10 |
|---|---|
| Median length | 6 |
| Mean length | 6.707006369 |
| Min length | 3 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 2 ? |
|---|---|
| Unique (%) | 1.3% |
Sample
| 1st row | Acura |
|---|---|
| 2nd row | Acura |
| 3rd row | Acura |
| 4th row | Acura |
| 5th row | Audi |
Common Values
| Value | Count | Frequency (%) |
| Dodge | 11 | 7.0% |
| Ford | 11 | 7.0% |
| Toyota | 9 | 5.7% |
| Chevrolet | 9 | 5.7% |
| Mercedes-B | 9 | 5.7% |
| Mitsubishi | 7 | 4.5% |
| Nissan | 7 | 4.5% |
| Chrysler | 7 | 4.5% |
| Volvo | 6 | 3.8% |
| Oldsmobile | 6 | 3.8% |
| Other values (20) | 75 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| dodge | 11 | 7.0% |
| ford | 11 | 7.0% |
| toyota | 9 | 5.7% |
| chevrolet | 9 | 5.7% |
| mercedes-b | 9 | 5.7% |
| mitsubishi | 7 | 4.5% |
| nissan | 7 | 4.5% |
| chrysler | 7 | 4.5% |
| volvo | 6 | 3.8% |
| oldsmobile | 6 | 3.8% |
| Other values (20) | 75 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 156 |
|---|---|
| Distinct (%) | 99.4% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 1.4 KiB |
| Neon | 2 |
|---|---|
| Integra | 1 |
| Cutlass | 1 |
| Sentra | 1 |
| Altima | 1 |
| Other values (151) |
Length
| Max length | 14 |
|---|---|
| Median length | 6 |
| Mean length | 6.554140127 |
| Min length | 2 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 155 ? |
|---|---|
| Unique (%) | 98.7% |
Sample
| 1st row | Integra |
|---|---|
| 2nd row | TL |
| 3rd row | CL |
| 4th row | RL |
| 5th row | A4 |
Common Values
| Value | Count | Frequency (%) |
| Neon | 2 | 1.3% |
| Integra | 1 | 0.6% |
| Cutlass | 1 | 0.6% |
| Sentra | 1 | 0.6% |
| Altima | 1 | 0.6% |
| Maxima | 1 | 0.6% |
| Quest | 1 | 0.6% |
| Pathfinder | 1 | 0.6% |
| Xterra | 1 | 0.6% |
| Frontier | 1 | 0.6% |
| Other values (146) | 146 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| grand | 4 | 2.3% |
| ram | 3 | 1.7% |
| coupe | 3 | 1.7% |
| town | 2 | 1.1% |
| cherokee | 2 | 1.1% |
| cabrio | 2 | 1.1% |
| montero | 2 | 1.1% |
| carrera | 2 | 1.1% |
| neon | 2 | 1.1% |
| sebring | 2 | 1.1% |
| Other values (153) | 153 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
| Distinct | 157 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 52.99807643 |
| Minimum | 0.11 |
|---|---|
| Maximum | 540.561 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 0.11 |
|---|---|
| 5-th percentile | 1.8708 |
| Q1 | 14.114 |
| median | 29.45 |
| Q3 | 67.956 |
| 95-th percentile | 185.3362 |
| Maximum | 540.561 |
| Range | 540.451 |
| Interquartile range (IQR) | 53.842 |
Descriptive statistics
| Standard deviation | 68.029422 |
|---|---|
| Coefficient of variation (CV) | 1.283620587 |
| Kurtosis | 17.55734423 |
| Mean | 52.99807643 |
| Median Absolute Deviation (MAD) | 20.468 |
| Skewness | 3.408518366 |
| Sum | 8320.698 |
| Variance | 4628.002257 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 16.919 | 1 | 0.6% |
| 1.112 | 1 | 0.6% |
| 42.643 | 1 | 0.6% |
| 88.094 | 1 | 0.6% |
| 79.853 | 1 | 0.6% |
| 27.308 | 1 | 0.6% |
| 42.574 | 1 | 0.6% |
| 54.158 | 1 | 0.6% |
| 65.005 | 1 | 0.6% |
| 38.554 | 1 | 0.6% |
| Other values (147) | 147 |
| Value | Count | Frequency (%) |
| 0.11 | 1 | |
| 0.916 | 1 | |
| 0.954 | 1 | |
| 1.112 | 1 | |
| 1.28 | 1 | |
| 1.38 | 1 | |
| 1.526 | 1 | |
| 1.866 | 1 | |
| 1.872 | 1 | |
| 3.311 | 1 |
| Value | Count | Frequency (%) |
| 540.561 | 1 | |
| 276.747 | 1 | |
| 247.994 | 1 | |
| 245.815 | 1 | |
| 230.902 | 1 | |
| 227.061 | 1 | |
| 220.65 | 1 | |
| 199.685 | 1 | |
| 181.749 | 1 | |
| 175.67 | 1 |
four_year_resale_value
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONMISSING| Distinct | 117 |
|---|---|
| Distinct (%) | 96.7% |
| Missing | 36 |
| Missing (%) | 22.9% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 18.07297521 |
| Minimum | 5.16 |
|---|---|
| Maximum | 67.55 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 5.16 |
|---|---|
| 5-th percentile | 7.85 |
| Q1 | 11.26 |
| median | 14.18 |
| Q3 | 19.875 |
| 95-th percentile | 41.25 |
| Maximum | 67.55 |
| Range | 62.39 |
| Interquartile range (IQR) | 8.615 |
Descriptive statistics
| Standard deviation | 11.4533841 |
|---|---|
| Coefficient of variation (CV) | 0.6337298629 |
| Kurtosis | 5.763855916 |
| Mean | 18.07297521 |
| Median Absolute Deviation (MAD) | 3.96 |
| Skewness | 2.294915493 |
| Sum | 2186.83 |
| Variance | 131.1800073 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 7.75 | 2 | 1.3% |
| 18.225 | 2 | 1.3% |
| 16.575 | 2 | 1.3% |
| 12.025 | 2 | 1.3% |
| 41.45 | 1 | 0.6% |
| 20.43 | 1 | 0.6% |
| 14.795 | 1 | 0.6% |
| 26.05 | 1 | 0.6% |
| 58.6 | 1 | 0.6% |
| 50.375 | 1 | 0.6% |
| Other values (107) | 107 | |
| (Missing) | 36 | 22.9% |
| Value | Count | Frequency (%) |
| 5.16 | 1 | |
| 5.86 | 1 | |
| 7.425 | 1 | |
| 7.75 | 2 | |
| 7.825 | 1 | |
| 7.85 | 1 | |
| 8.325 | 1 | |
| 8.45 | 1 | |
| 8.8 | 1 | |
| 8.835 | 1 |
| Value | Count | Frequency (%) |
| 67.55 | 1 | |
| 60.625 | 1 | |
| 58.6 | 1 | |
| 58.47 | 1 | |
| 50.375 | 1 | |
| 41.45 | 1 | |
| 41.25 | 1 | |
| 40.375 | 1 | |
| 39 | 1 | |
| 36.225 | 1 |
| Distinct | 2 |
|---|---|
| Distinct (%) | 1.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 1.4 KiB |
| Passenger | |
|---|---|
| Car |
Length
| Max length | 9 |
|---|---|
| Median length | 9 |
| Mean length | 7.433121019 |
| Min length | 3 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | Passenger |
|---|---|
| 2nd row | Passenger |
| 3rd row | Passenger |
| 4th row | Passenger |
| 5th row | Passenger |
Common Values
| Value | Count | Frequency (%) |
| Passenger | 116 | |
| Car | 41 | 26.1% |
Length
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| passenger | 116 | |
| car | 41 | 26.1% |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
Price_in_thousands
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONMISSING| Distinct | 152 |
|---|---|
| Distinct (%) | 98.1% |
| Missing | 2 |
| Missing (%) | 1.3% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 27.39075484 |
| Minimum | 9.235 |
|---|---|
| Maximum | 85.5 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 9.235 |
|---|---|
| 5-th percentile | 12.469 |
| Q1 | 18.0175 |
| median | 22.799 |
| Q3 | 31.9475 |
| 95-th percentile | 55.835 |
| Maximum | 85.5 |
| Range | 76.265 |
| Interquartile range (IQR) | 13.93 |
Descriptive statistics
| Standard deviation | 14.35165319 |
|---|---|
| Coefficient of variation (CV) | 0.5239597548 |
| Kurtosis | 3.63041233 |
| Mean | 27.39075484 |
| Median Absolute Deviation (MAD) | 6.099 |
| Skewness | 1.765734331 |
| Sum | 4245.567 |
| Variance | 205.9699493 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 18.89 | 2 | 1.3% |
| 38.9 | 2 | 1.3% |
| 12.64 | 2 | 1.3% |
| 24.15 | 1 | 0.6% |
| 20.39 | 1 | 0.6% |
| 26.249 | 1 | 0.6% |
| 26.399 | 1 | 0.6% |
| 29.299 | 1 | 0.6% |
| 22.799 | 1 | 0.6% |
| 17.89 | 1 | 0.6% |
| Other values (142) | 142 | |
| (Missing) | 2 | 1.3% |
| Value | Count | Frequency (%) |
| 9.235 | 1 | |
| 9.699 | 1 | |
| 10.685 | 1 | |
| 11.528 | 1 | |
| 11.799 | 1 | |
| 12.05 | 1 | |
| 12.07 | 1 | |
| 12.315 | 1 | |
| 12.535 | 1 | |
| 12.64 | 2 |
| Value | Count | Frequency (%) |
| 85.5 | 1 | |
| 82.6 | 1 | |
| 74.97 | 1 | |
| 71.02 | 1 | |
| 69.725 | 1 | |
| 69.7 | 1 | |
| 62 | 1 | |
| 60.105 | 1 | |
| 54.005 | 1 | |
| 51.728 | 1 |
| Distinct | 31 |
|---|---|
| Distinct (%) | 19.9% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3.060897436 |
| Minimum | 1 |
|---|---|
| Maximum | 8 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 1.8 |
| Q1 | 2.3 |
| median | 3 |
| Q3 | 3.575 |
| 95-th percentile | 4.775 |
| Maximum | 8 |
| Range | 7 |
| Interquartile range (IQR) | 1.275 |
Descriptive statistics
| Standard deviation | 1.044652973 |
|---|---|
| Coefficient of variation (CV) | 0.3412897672 |
| Kurtosis | 2.344782023 |
| Mean | 3.060897436 |
| Median Absolute Deviation (MAD) | 0.7 |
| Skewness | 1.100447343 |
| Sum | 477.5 |
| Variance | 1.091299835 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=31)
| Value | Count | Frequency (%) |
| 2 | 17 | 10.8% |
| 3 | 14 | 8.9% |
| 2.4 | 11 | 7.0% |
| 2.5 | 11 | 7.0% |
| 4.6 | 9 | 5.7% |
| 1.8 | 8 | 5.1% |
| 3.5 | 8 | 5.1% |
| 3.8 | 8 | 5.1% |
| 4 | 7 | 4.5% |
| 3.4 | 7 | 4.5% |
| Other values (21) | 56 |
| Value | Count | Frequency (%) |
| 1 | 1 | 0.6% |
| 1.5 | 1 | 0.6% |
| 1.6 | 1 | 0.6% |
| 1.8 | 8 | |
| 1.9 | 5 | 3.2% |
| 2 | 17 | |
| 2.2 | 4 | 2.5% |
| 2.3 | 6 | 3.8% |
| 2.4 | 11 | |
| 2.5 | 11 |
| Value | Count | Frequency (%) |
| 8 | 1 | 0.6% |
| 5.7 | 2 | 1.3% |
| 5.4 | 1 | 0.6% |
| 5.2 | 2 | 1.3% |
| 5 | 2 | 1.3% |
| 4.7 | 2 | 1.3% |
| 4.6 | 9 | |
| 4.3 | 2 | 1.3% |
| 4.2 | 1 | 0.6% |
| 4 | 7 |
| Distinct | 66 |
|---|---|
| Distinct (%) | 42.3% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 185.9487179 |
| Minimum | 55 |
|---|---|
| Maximum | 450 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 55 |
|---|---|
| 5-th percentile | 114.5 |
| Q1 | 149.5 |
| median | 177.5 |
| Q3 | 215 |
| 95-th percentile | 300 |
| Maximum | 450 |
| Range | 395 |
| Interquartile range (IQR) | 65.5 |
Descriptive statistics
| Standard deviation | 56.70032086 |
|---|---|
| Coefficient of variation (CV) | 0.3049245054 |
| Kurtosis | 2.406657478 |
| Mean | 185.9487179 |
| Median Absolute Deviation (MAD) | 32.5 |
| Skewness | 1.000694992 |
| Sum | 29008 |
| Variance | 3214.926385 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 150 | 9 | 5.7% |
| 170 | 9 | 5.7% |
| 200 | 8 | 5.1% |
| 210 | 7 | 4.5% |
| 115 | 6 | 3.8% |
| 185 | 5 | 3.2% |
| 175 | 5 | 3.2% |
| 275 | 5 | 3.2% |
| 120 | 4 | 2.5% |
| 190 | 4 | 2.5% |
| Other values (56) | 94 |
| Value | Count | Frequency (%) |
| 55 | 1 | 0.6% |
| 92 | 1 | 0.6% |
| 100 | 2 | 1.3% |
| 106 | 1 | 0.6% |
| 107 | 1 | 0.6% |
| 110 | 1 | 0.6% |
| 113 | 1 | 0.6% |
| 115 | 6 | |
| 119 | 1 | 0.6% |
| 120 | 4 |
| Value | Count | Frequency (%) |
| 450 | 1 | 0.6% |
| 345 | 1 | 0.6% |
| 310 | 1 | 0.6% |
| 302 | 2 | 1.3% |
| 300 | 4 | |
| 290 | 1 | 0.6% |
| 275 | 5 | |
| 255 | 1 | 0.6% |
| 253 | 3 | |
| 250 | 1 | 0.6% |
| Distinct | 88 |
|---|---|
| Distinct (%) | 56.4% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 107.4871795 |
| Minimum | 92.6 |
|---|---|
| Maximum | 138.7 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 92.6 |
|---|---|
| 5-th percentile | 95.875 |
| Q1 | 103 |
| median | 107 |
| Q3 | 112.2 |
| 95-th percentile | 119.25 |
| Maximum | 138.7 |
| Range | 46.1 |
| Interquartile range (IQR) | 9.2 |
Descriptive statistics
| Standard deviation | 7.64130303 |
|---|---|
| Coefficient of variation (CV) | 0.07109036693 |
| Kurtosis | 2.859284871 |
| Mean | 107.4871795 |
| Median Absolute Deviation (MAD) | 4.6 |
| Skewness | 0.9699356566 |
| Sum | 16768 |
| Variance | 58.38951199 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 112.2 | 8 | 5.1% |
| 107 | 5 | 3.2% |
| 113 | 5 | 3.2% |
| 102.4 | 4 | 2.5% |
| 109 | 4 | 2.5% |
| 106.5 | 4 | 2.5% |
| 108 | 4 | 2.5% |
| 98.9 | 4 | 2.5% |
| 106.4 | 4 | 2.5% |
| 107.3 | 4 | 2.5% |
| Other values (78) | 110 |
| Value | Count | Frequency (%) |
| 92.6 | 2 | |
| 93.1 | 1 | |
| 93.4 | 1 | |
| 94.5 | 2 | |
| 94.9 | 1 | |
| 95.2 | 1 | |
| 96.1 | 1 | |
| 96.2 | 1 | |
| 97 | 1 | |
| 97.1 | 1 |
| Value | Count | Frequency (%) |
| 138.7 | 1 | |
| 138.5 | 1 | |
| 131 | 1 | |
| 127.2 | 1 | |
| 121.5 | 1 | |
| 120.7 | 1 | |
| 120 | 2 | |
| 119 | 2 | |
| 118.1 | 1 | |
| 117.7 | 1 |
| Distinct | 78 |
|---|---|
| Distinct (%) | 50.0% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 71.15 |
| Minimum | 62.6 |
|---|---|
| Maximum | 79.9 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 62.6 |
|---|---|
| 5-th percentile | 66.5 |
| Q1 | 68.4 |
| median | 70.55 |
| Q3 | 73.425 |
| 95-th percentile | 78.2 |
| Maximum | 79.9 |
| Range | 17.3 |
| Interquartile range (IQR) | 5.025 |
Descriptive statistics
| Standard deviation | 3.451871862 |
|---|---|
| Coefficient of variation (CV) | 0.0485154162 |
| Kurtosis | -0.3004675291 |
| Mean | 71.15 |
| Median Absolute Deviation (MAD) | 2.4 |
| Skewness | 0.4838620694 |
| Sum | 11099.4 |
| Variance | 11.91541935 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 66.7 | 6 | 3.8% |
| 74.4 | 6 | 3.8% |
| 68.3 | 5 | 3.2% |
| 70.3 | 5 | 3.2% |
| 72.7 | 5 | 3.2% |
| 69.1 | 4 | 2.5% |
| 69.4 | 4 | 2.5% |
| 66.5 | 4 | 2.5% |
| 67.5 | 3 | 1.9% |
| 73.6 | 3 | 1.9% |
| Other values (68) | 111 |
| Value | Count | Frequency (%) |
| 62.6 | 1 | 0.6% |
| 65.7 | 1 | 0.6% |
| 66.4 | 3 | |
| 66.5 | 4 | |
| 66.7 | 6 | |
| 66.9 | 2 | 1.3% |
| 67 | 1 | 0.6% |
| 67.1 | 1 | 0.6% |
| 67.3 | 2 | 1.3% |
| 67.4 | 1 | 0.6% |
| Value | Count | Frequency (%) |
| 79.9 | 1 | 0.6% |
| 79.3 | 1 | 0.6% |
| 79.1 | 1 | 0.6% |
| 78.8 | 2 | |
| 78.7 | 1 | 0.6% |
| 78.2 | 3 | |
| 77 | 1 | 0.6% |
| 76.8 | 2 | |
| 76.6 | 1 | 0.6% |
| 76.4 | 2 |
| Distinct | 127 |
|---|---|
| Distinct (%) | 81.4% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 187.3435897 |
| Minimum | 149.4 |
|---|---|
| Maximum | 224.5 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 149.4 |
|---|---|
| 5-th percentile | 163.675 |
| Q1 | 177.575 |
| median | 187.9 |
| Q3 | 196.125 |
| 95-th percentile | 208.5 |
| Maximum | 224.5 |
| Range | 75.1 |
| Interquartile range (IQR) | 18.55 |
Descriptive statistics
| Standard deviation | 13.43175428 |
|---|---|
| Coefficient of variation (CV) | 0.07169583065 |
| Kurtosis | 0.3025740191 |
| Mean | 187.3435897 |
| Median Absolute Deviation (MAD) | 9.4 |
| Skewness | -0.05904682307 |
| Sum | 29225.6 |
| Variance | 180.4120232 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 186.3 | 4 | 2.5% |
| 189.2 | 3 | 1.9% |
| 192 | 3 | 1.9% |
| 190.4 | 3 | 1.9% |
| 163.3 | 2 | 1.3% |
| 192.5 | 2 | 1.3% |
| 174 | 2 | 1.3% |
| 212 | 2 | 1.3% |
| 193.5 | 2 | 1.3% |
| 208.5 | 2 | 1.3% |
| Other values (117) | 131 |
| Value | Count | Frequency (%) |
| 149.4 | 1 | |
| 152 | 1 | |
| 157.3 | 1 | |
| 157.9 | 1 | |
| 160.4 | 1 | |
| 161.1 | 1 | |
| 163.3 | 2 | |
| 163.8 | 1 | |
| 165.4 | 1 | |
| 166.7 | 1 |
| Value | Count | Frequency (%) |
| 224.5 | 1 | |
| 224.2 | 1 | |
| 215.3 | 1 | |
| 215 | 1 | |
| 212 | 2 | |
| 209.1 | 1 | |
| 208.5 | 2 | |
| 207.7 | 1 | |
| 207.2 | 1 | |
| 206.8 | 1 |
| Distinct | 147 |
|---|---|
| Distinct (%) | 94.8% |
| Missing | 2 |
| Missing (%) | 1.3% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 3.378025806 |
| Minimum | 1.895 |
|---|---|
| Maximum | 5.572 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 1.895 |
|---|---|
| 5-th percentile | 2.4235 |
| Q1 | 2.971 |
| median | 3.342 |
| Q3 | 3.7995 |
| 95-th percentile | 4.3891 |
| Maximum | 5.572 |
| Range | 3.677 |
| Interquartile range (IQR) | 0.8285 |
Descriptive statistics
| Standard deviation | 0.6305016344 |
|---|---|
| Coefficient of variation (CV) | 0.1866479626 |
| Kurtosis | 1.265453569 |
| Mean | 3.378025806 |
| Median Absolute Deviation (MAD) | 0.41 |
| Skewness | 0.7081582404 |
| Sum | 523.594 |
| Variance | 0.397532311 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 2.769 | 3 | 1.9% |
| 2.998 | 3 | 1.9% |
| 2.91 | 2 | 1.3% |
| 3.075 | 2 | 1.3% |
| 3.876 | 2 | 1.3% |
| 3.368 | 2 | 1.3% |
| 3.455 | 1 | 0.6% |
| 2.958 | 1 | 0.6% |
| 3.102 | 1 | 0.6% |
| 4.387 | 1 | 0.6% |
| Other values (137) | 137 | |
| (Missing) | 2 | 1.3% |
| Value | Count | Frequency (%) |
| 1.895 | 1 | |
| 2.24 | 1 | |
| 2.25 | 1 | |
| 2.332 | 1 | |
| 2.339 | 1 | |
| 2.367 | 1 | |
| 2.398 | 1 | |
| 2.42 | 1 | |
| 2.425 | 1 | |
| 2.452 | 1 |
| Value | Count | Frequency (%) |
| 5.572 | 1 | |
| 5.401 | 1 | |
| 5.393 | 1 | |
| 5.115 | 1 | |
| 4.808 | 1 | |
| 4.52 | 1 | |
| 4.47 | 1 | |
| 4.394 | 1 | |
| 4.387 | 1 | |
| 4.298 | 1 |
| Distinct | 55 |
|---|---|
| Distinct (%) | 35.3% |
| Missing | 1 |
| Missing (%) | 0.6% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 17.95192308 |
| Minimum | 10.3 |
|---|---|
| Maximum | 32 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 10.3 |
|---|---|
| 5-th percentile | 12.5 |
| Q1 | 15.8 |
| median | 17.2 |
| Q3 | 19.575 |
| 95-th percentile | 25.4 |
| Maximum | 32 |
| Range | 21.7 |
| Interquartile range (IQR) | 3.775 |
Descriptive statistics
| Standard deviation | 3.887921265 |
|---|---|
| Coefficient of variation (CV) | 0.2165740822 |
| Kurtosis | 2.07281321 |
| Mean | 17.95192308 |
| Median Absolute Deviation (MAD) | 1.9 |
| Skewness | 1.136712406 |
| Sum | 2800.5 |
| Variance | 15.11593176 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 18.5 | 14 | 8.9% |
| 17 | 9 | 5.7% |
| 20 | 8 | 5.1% |
| 19 | 8 | 5.1% |
| 16 | 7 | 4.5% |
| 13.2 | 6 | 3.8% |
| 15.9 | 6 | 3.8% |
| 15 | 5 | 3.2% |
| 14.5 | 5 | 3.2% |
| 17.5 | 5 | 3.2% |
| Other values (45) | 83 |
| Value | Count | Frequency (%) |
| 10.3 | 1 | 0.6% |
| 11.9 | 2 | 1.3% |
| 12 | 1 | 0.6% |
| 12.1 | 3 | |
| 12.5 | 2 | 1.3% |
| 12.7 | 1 | 0.6% |
| 13.1 | 2 | 1.3% |
| 13.2 | 6 | |
| 13.7 | 1 | 0.6% |
| 14 | 1 | 0.6% |
| Value | Count | Frequency (%) |
| 32 | 2 | |
| 30 | 2 | |
| 26 | 3 | |
| 25.4 | 2 | |
| 25.1 | 1 | 0.6% |
| 25 | 3 | |
| 24.3 | 1 | 0.6% |
| 23.7 | 1 | 0.6% |
| 23.2 | 2 | |
| 22.5 | 1 | 0.6% |
Fuel_efficiency
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONMISSING| Distinct | 20 |
|---|---|
| Distinct (%) | 13.0% |
| Missing | 3 |
| Missing (%) | 1.9% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 23.84415584 |
| Minimum | 15 |
|---|---|
| Maximum | 45 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 15 |
|---|---|
| 5-th percentile | 16.65 |
| Q1 | 21 |
| median | 24 |
| Q3 | 26 |
| 95-th percentile | 31 |
| Maximum | 45 |
| Range | 30 |
| Interquartile range (IQR) | 5 |
Descriptive statistics
| Standard deviation | 4.282705562 |
|---|---|
| Coefficient of variation (CV) | 0.1796123792 |
| Kurtosis | 3.241130815 |
| Mean | 23.84415584 |
| Median Absolute Deviation (MAD) | 2 |
| Skewness | 0.6923277567 |
| Sum | 3672 |
| Variance | 18.34156693 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=20)
| Value | Count | Frequency (%) |
| 25 | 23 | |
| 24 | 16 | |
| 27 | 15 | |
| 22 | 14 | |
| 21 | 14 | |
| 23 | 14 | |
| 26 | 12 | 7.6% |
| 19 | 6 | 3.8% |
| 20 | 5 | 3.2% |
| 15 | 5 | 3.2% |
| Other values (10) | 30 |
| Value | Count | Frequency (%) |
| 15 | 5 | 3.2% |
| 16 | 3 | 1.9% |
| 17 | 3 | 1.9% |
| 18 | 5 | 3.2% |
| 19 | 6 | 3.8% |
| 20 | 5 | 3.2% |
| 21 | 14 | |
| 22 | 14 | |
| 23 | 14 | |
| 24 | 16 |
| Value | Count | Frequency (%) |
| 45 | 1 | 0.6% |
| 33 | 4 | 2.5% |
| 32 | 1 | 0.6% |
| 31 | 3 | 1.9% |
| 30 | 5 | 3.2% |
| 29 | 2 | 1.3% |
| 28 | 3 | 1.9% |
| 27 | 15 | |
| 26 | 12 | |
| 25 | 23 |
| Distinct | 130 |
|---|---|
| Distinct (%) | 82.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 1.4 KiB |
| 10/5/2012 | 2 |
|---|---|
| 1/24/2011 | 2 |
| 4/26/2011 | 2 |
| 6/25/2011 | 2 |
| 9/21/2011 | 2 |
| Other values (125) |
Length
| Max length | 10 |
|---|---|
| Median length | 9 |
| Mean length | 8.968152866 |
| Min length | 8 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 103 ? |
|---|---|
| Unique (%) | 65.6% |
Sample
| 1st row | 2/2/2012 |
|---|---|
| 2nd row | 6/3/2011 |
| 3rd row | 1/4/2012 |
| 4th row | 3/10/2011 |
| 5th row | 10/8/2011 |
Common Values
| Value | Count | Frequency (%) |
| 10/5/2012 | 2 | 1.3% |
| 1/24/2011 | 2 | 1.3% |
| 4/26/2011 | 2 | 1.3% |
| 6/25/2011 | 2 | 1.3% |
| 9/21/2011 | 2 | 1.3% |
| 2/18/2011 | 2 | 1.3% |
| 4/1/2011 | 2 | 1.3% |
| 5/31/2011 | 2 | 1.3% |
| 8/27/2011 | 2 | 1.3% |
| 9/25/2011 | 2 | 1.3% |
| Other values (120) | 137 |
Length
Histogram of lengths of the category
| Value | Count | Frequency (%) |
| 10/5/2012 | 2 | 1.3% |
| 8/31/2011 | 2 | 1.3% |
| 1/24/2011 | 2 | 1.3% |
| 10/30/2012 | 2 | 1.3% |
| 2/23/2012 | 2 | 1.3% |
| 11/24/2012 | 2 | 1.3% |
| 8/16/2012 | 2 | 1.3% |
| 1/4/2012 | 2 | 1.3% |
| 9/10/2012 | 2 | 1.3% |
| 4/24/2011 | 2 | 1.3% |
| Other values (120) | 137 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
Power_perf_factor
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONMISSING| Distinct | 154 |
|---|---|
| Distinct (%) | 99.4% |
| Missing | 2 |
| Missing (%) | 1.3% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 77.0435912 |
| Minimum | 23.27627233 |
|---|---|
| Maximum | 188.144323 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 1.4 KiB |
Quantile statistics
| Minimum | 23.27627233 |
|---|---|
| 5-th percentile | 46.2039974 |
| Q1 | 60.40770678 |
| median | 72.03091719 |
| Q3 | 89.41487752 |
| 95-th percentile | 125.0915129 |
| Maximum | 188.144323 |
| Range | 164.8680507 |
| Interquartile range (IQR) | 29.00717075 |
Descriptive statistics
| Standard deviation | 25.1426641 |
|---|---|
| Coefficient of variation (CV) | 0.3263433558 |
| Kurtosis | 2.081292892 |
| Mean | 77.0435912 |
| Median Absolute Deviation (MAD) | 14.24160572 |
| Skewness | 1.070634989 |
| Sum | 11941.75664 |
| Variance | 632.153558 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 52.08489875 | 2 | 1.3% |
| 58.28014952 | 1 | 0.6% |
| 86.27252291 | 1 | 0.6% |
| 63.31372783 | 1 | 0.6% |
| 89.42782031 | 1 | 0.6% |
| 71.17166413 | 1 | 0.6% |
| 72.29035508 | 1 | 0.6% |
| 69.78294434 | 1 | 0.6% |
| 67.88927059 | 1 | 0.6% |
| 60.86161155 | 1 | 0.6% |
| Other values (144) | 144 | |
| (Missing) | 2 | 1.3% |
| Value | Count | Frequency (%) |
| 23.27627233 | 1 | |
| 36.67228358 | 1 | |
| 39.98642475 | 1 | |
| 40.70007242 | 1 | |
| 42.87909734 | 1 | |
| 43.11713201 | 1 | |
| 44.08370946 | 1 | |
| 45.83218056 | 1 | |
| 46.36334747 | 1 | |
| 46.94387676 | 1 |
| Value | Count | Frequency (%) |
| 188.144323 | 1 | |
| 141.14115 | 1 | |
| 141.1009845 | 1 | |
| 139.9822936 | 1 | |
| 135.9147096 | 1 | |
| 134.6568582 | 1 | |
| 134.3909754 | 1 | |
| 125.2738757 | 1 | |
| 125.0133574 | 1 | |
| 124.4467163 | 1 |
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here. A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.
First rows
| Manufacturer | Model | Sales_in_thousands | four_year_resale_value | Vehicle_type | Price_in_thousands | Engine_size | Horsepower | Wheelbase | Width | Length | Curb_weight | Fuel_capacity | Fuel_efficiency | Latest_Launch | Power_perf_factor | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Acura | Integra | 16.919 | 16.360 | Passenger | 21.50 | 1.8 | 140.0 | 101.2 | 67.3 | 172.4 | 2.639 | 13.2 | 28.0 | 2/2/2012 | 58.280150 |
| 1 | Acura | TL | 39.384 | 19.875 | Passenger | 28.40 | 3.2 | 225.0 | 108.1 | 70.3 | 192.9 | 3.517 | 17.2 | 25.0 | 6/3/2011 | 91.370778 |
| 2 | Acura | CL | 14.114 | 18.225 | Passenger | NaN | 3.2 | 225.0 | 106.9 | 70.6 | 192.0 | 3.470 | 17.2 | 26.0 | 1/4/2012 | NaN |
| 3 | Acura | RL | 8.588 | 29.725 | Passenger | 42.00 | 3.5 | 210.0 | 114.6 | 71.4 | 196.6 | 3.850 | 18.0 | 22.0 | 3/10/2011 | 91.389779 |
| 4 | Audi | A4 | 20.397 | 22.255 | Passenger | 23.99 | 1.8 | 150.0 | 102.6 | 68.2 | 178.0 | 2.998 | 16.4 | 27.0 | 10/8/2011 | 62.777639 |
| 5 | Audi | A6 | 18.780 | 23.555 | Passenger | 33.95 | 2.8 | 200.0 | 108.7 | 76.1 | 192.0 | 3.561 | 18.5 | 22.0 | 8/9/2011 | 84.565105 |
| 6 | Audi | A8 | 1.380 | 39.000 | Passenger | 62.00 | 4.2 | 310.0 | 113.0 | 74.0 | 198.2 | 3.902 | 23.7 | 21.0 | 2/27/2012 | 134.656858 |
| 7 | BMW | 323i | 19.747 | NaN | Passenger | 26.99 | 2.5 | 170.0 | 107.3 | 68.4 | 176.0 | 3.179 | 16.6 | 26.0 | 6/28/2011 | 71.191207 |
| 8 | BMW | 328i | 9.231 | 28.675 | Passenger | 33.40 | 2.8 | 193.0 | 107.3 | 68.5 | 176.0 | 3.197 | 16.6 | 24.0 | 1/29/2012 | 81.877069 |
| 9 | BMW | 528i | 17.527 | 36.125 | Passenger | 38.90 | 2.8 | 193.0 | 111.4 | 70.9 | 188.0 | 3.472 | 18.5 | 25.0 | 4/4/2011 | 83.998724 |
Last rows
| Manufacturer | Model | Sales_in_thousands | four_year_resale_value | Vehicle_type | Price_in_thousands | Engine_size | Horsepower | Wheelbase | Width | Length | Curb_weight | Fuel_capacity | Fuel_efficiency | Latest_Launch | Power_perf_factor | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 147 | Volkswagen | Passat | 51.102 | 16.725 | Passenger | 21.20 | 1.8 | 150.0 | 106.4 | 68.5 | 184.1 | 3.043 | 16.4 | 27.0 | 10/30/2012 | 61.701381 |
| 148 | Volkswagen | Cabrio | 9.569 | 16.575 | Passenger | 19.99 | 2.0 | 115.0 | 97.4 | 66.7 | 160.4 | 3.079 | 13.7 | 26.0 | 5/31/2011 | 48.907372 |
| 149 | Volkswagen | GTI | 5.596 | 13.760 | Passenger | 17.50 | 2.0 | 115.0 | 98.9 | 68.3 | 163.3 | 2.762 | 14.6 | 26.0 | 4/1/2011 | 47.946841 |
| 150 | Volkswagen | Beetle | 49.463 | NaN | Passenger | 15.90 | 2.0 | 115.0 | 98.9 | 67.9 | 161.1 | 2.769 | 14.5 | 26.0 | 10/20/2011 | 47.329632 |
| 151 | Volvo | S40 | 16.957 | NaN | Passenger | 23.40 | 1.9 | 160.0 | 100.5 | 67.6 | 176.6 | 2.998 | 15.8 | 25.0 | 2/18/2011 | 66.113057 |
| 152 | Volvo | V40 | 3.545 | NaN | Passenger | 24.40 | 1.9 | 160.0 | 100.5 | 67.6 | 176.6 | 3.042 | 15.8 | 25.0 | 9/21/2011 | 66.498812 |
| 153 | Volvo | S70 | 15.245 | NaN | Passenger | 27.50 | 2.4 | 168.0 | 104.9 | 69.3 | 185.9 | 3.208 | 17.9 | 25.0 | 11/24/2012 | 70.654495 |
| 154 | Volvo | V70 | 17.531 | NaN | Passenger | 28.80 | 2.4 | 168.0 | 104.9 | 69.3 | 186.2 | 3.259 | 17.9 | 25.0 | 6/25/2011 | 71.155978 |
| 155 | Volvo | C70 | 3.493 | NaN | Passenger | 45.50 | 2.3 | 236.0 | 104.9 | 71.5 | 185.7 | 3.601 | 18.5 | 23.0 | 4/26/2011 | 101.623357 |
| 156 | Volvo | S80 | 18.969 | NaN | Passenger | 36.00 | 2.9 | 201.0 | 109.9 | 72.1 | 189.8 | 3.600 | 21.1 | 24.0 | 11/14/2011 | 85.735655 |